It is desired to achieve seamless collection of the health information in an electronic health or medical record (EHR or EMR) via flow of digital information through hospital IT infrastructure. The EHR is ultimately intended to provide a “paperless” electronic medical records environment. Unfortunately, in current practice, reports are still printed on paper or image portable document format (PDF) form for the foreseeable future, due for example to legacy systems without sufficient electronic connectivity, receipt of medical reports from outside laboratories lacking electronic connectivity with the hospital, or so forth. Hence, such information has to be transferred back into a corresponding electronic record. For example, paper medical reports from outside laboratories may be scanned and stored in the EMR as a portable document format (PDF) object or some other portable format such as Office Open XML (OOXML or OpenXML) or Open Document Format (ODF). Although relevant pieces of information might be automatically identified in the PDF and matched with the corresponding EHR fields by automated processing algorithms, it cannot be expected that such algorithms will operate with sufficient sensitivity and specificity required in clinical applications.
Presently, such a PDF report is handled as follows. The physician (other another user such as a nurse or technician) reads the PDF report, identifies relevant information (e.g. patient name, demographic data, personal data such as smoker/non-smoker, medical data, or such) and manually re-types or enters the information into appropriate EHR data entry fields. This is a slow and error-prone process. Moreover, physicians are expected to increasingly use mobile devices such as cellphones or tablet computers to perform this task while on-the-go, and the small screen and awkward user interface (touch screen and/or virtual keyboard) make transcription of relevant information from a PDF form into the EHR even more tedious. Conventional copy-and-paste tools may be used, but these are inefficient as the physician must open the PDF window, copy relevant text, and then switch to the EHR data entry window and paste the text into the appropriate GUI dialog. Copy-and-paste user interfacing with mobile devices requires special dexterity, as the user must precisely mark start-and-stop points using the touchscreen.
Further, there is an increasing requirement for structured reporting on patient information, e.g. in cancer registries, disease specific portals or broad studies. These systems have the same issue that information on the patient needs to be converted to a specific electronic form from a variety of sources.
As a result, physicians may still need to read the entire report to identify the required information and/or provide additional cues for semi-automated schemes. While manual form filling by a physician having all reports available (e.g. paper or PDF) is the most reliable form and still standard today, it requires a lot of time, is tedious and inefficient. On the other hand, natural language processing (NLP) algorithms and automated text processing modules do exist, but are not reliable enough to be used regularly in the clinic and require significant manual corrections.
The following provides new and improved devices and methods which overcome the foregoing problems and others.